Handling a hard dataset… or not

For #makeovermonday week 49 Andy found a tricky dataset from Financial Times about Pubs food/drink costs in the UK.

Although I lived in London 10 years ago, I am NOT a Pub guy. First I really don’t drink tons of alcohol (in special I simply can’t handle beer), second I was living far far far away from Central London in a village called Harefield, where I went only once to the local Pub with some roommates I had at the time.

So this lack of understanding about the Pub culture, Beer names, Pub Food names was a big struggle for me to understand the data and start vizzing. So I took a breath, opened and read the FT article, located some specific information that I think is important to highlight (for example, the article mentions that the survey doesn’t even contemplate 1/4 of all Pubs from this JD Brand; so affirming that this is the “cheapest” pub for a beer or for food is way misleading!) and went back to Tableau with the plan to highlight the cheapest and most expensive Pubs.

Basically my viz has a bar on the left where each Pub from the survey is listed. Color follows my main objective, green for the cheapest and blue for most expensive Pubs. People can interact with bars and map to locate the Pubs and find more information about their menus from tooltip. To complement that I’ve added some key findings at the center of the viz, color coded those accordingly and I was done. Ufa!!

Here is the viz, you can click to open on Tableau Public.

How Cheap is JD Wetherspoon


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